Default Clustering in Large Portfolios: Typical Events

Annals of Applied Probability, Forthcoming

40 Pages Posted: 9 Jan 2011 Last revised: 29 Apr 2012

See all articles by Kay Giesecke

Kay Giesecke

Stanford University - Management Science & Engineering

Konstantinos Spiliopoulos

Brown University - Division of Applied Mathematics

Richard Sowers

University of Illinois at Urbana-Champaign - Department of Mathematics

Date Written: January 5, 2011

Abstract

We develop a dynamic point process model of correlated default timing in a portfolio of firms, and analyze typical default profiles in the limit as the size of the pool grows. In our model, a firm defaults at a stochastic intensity that is influenced by an idiosyncratic risk process, a systematic risk process common to all firms, and past defaults. We prove a law of large numbers for the default rate in the pool, which describes the "typical" behavior of defaults.

Keywords: Large Portfolio, Self-Exciting Defaults, Mean-Field, law of large numbers

Suggested Citation

Giesecke, Kay and Spiliopoulos, Konstantinos and Sowers, Richard, Default Clustering in Large Portfolios: Typical Events (January 5, 2011). Annals of Applied Probability, Forthcoming, Available at SSRN: https://ssrn.com/abstract=1736843 or http://dx.doi.org/10.2139/ssrn.1736843

Kay Giesecke (Contact Author)

Stanford University - Management Science & Engineering ( email )

475 Via Ortega
Stanford, CA 94305
United States
(650) 723 9265 (Phone)
(650) 723 1614 (Fax)

HOME PAGE: http://https://giesecke.people.stanford.edu

Konstantinos Spiliopoulos

Brown University - Division of Applied Mathematics ( email )

Providence, RI 02912
United States

Richard Sowers

University of Illinois at Urbana-Champaign - Department of Mathematics ( email )

1409 W. Green St.
Urbana, IL 61801
United States

HOME PAGE: http://www.math.uiuc.edu/~r-sowers/

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